most citedAccelerating the prediction of inorganic surfaces with machine learning interatomic potentials

23 citations · 30 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.mtrl-sci2025

Cation vacancies mediate thermochemical water splitting with iron aluminates

Nathan J. Szymanski, Kent J. Warren, Alan W. Weimer +1

Solar thermochemical water splitting enables hydrogen production by cycling metal oxides between reduced and oxidized states, typically through an oxygen vacancy mechanism. However…

cond-mat.mtrl-sci2025★ 2 cited

Thermodynamics of proton insertion across the perovskite-brownmillerite transition in La0.5Sr0.5CoO3-δ

Armand J. Lannerd, Nathan J. Szymanski, Christopher J. Bartel

LaSrCoO3- is a promising off-stoichiometric metal oxide that undergoes a topotactic perovskite ( = 0) to brownmillerite ( = 0.5) transition under electrochem…

cond-mat.mtrl-sci2025

Computational search for materials having a giant anomalous Hall effect in the pyrochlore and spinel crystal structures

Sean Sullivan, Seungjun Lee, Nathan J. Szymanski +4

Ferromagnetic pyrochlore and spinel materials with topological flat bands are of interest for their potential to exhibit a giant anomalous Hall effect (AHE). In this work, we prese…

cond-mat.mtrl-sci2025★ 5 cited

Topological descriptors for the electron density of inorganic solids

Nathan J. Szymanski, Alexander Smith, Prodromos Daoutidis +1

Descriptors play an important role in data-driven materials design. While most descriptors of crystalline materials emphasize structure and composition, they often neglect the elec…

cond-mat.mtrl-sci2025

Establishing baselines for generative discovery of inorganic crystals

Nathan J. Szymanski, Christopher J. Bartel

Generative artificial intelligence offers a promising avenue for materials discovery, yet its advantages over traditional methods remain unclear. In this work, we introduce and ben…

cond-mat.mtrl-sci2023★ 23 cited

Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials

Kyle Noordhoek, Christopher J. Bartel

The surface properties of solid-state materials often dictate their functionality, especially for applications where nanoscale effects become important. The relevant surface(s) and…